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distribution_strategy_context.py
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distribution_strategy_context.py
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# Copyright 2018 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Utility to get tf.distribute.Strategy related contexts."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import threading
from tensorflow.python.framework import ops
from tensorflow.python.util.lazy_loader import LazyLoader
from tensorflow.python.util.tf_export import tf_export
# There is a circular dependency between this and the `distribute_lib` module.
# So we load it lazily to work around this.
distribute_lib = LazyLoader(
"distribute_lib", globals(),
"tensorflow.python.distribute.distribute_lib")
# ------------------------------------------------------------------------------
# Internal API for setting the current thread mode as being either in a
# replica or cross-replica context for a particular tf.distribute.Strategy.
class _ThreadMode(object):
def __init__(self, dist, cross, replica):
self.strategy = dist
self.cross_replica_context = cross
self.replica_context = replica
class _CrossReplicaThreadMode(_ThreadMode):
def __init__(self, strategy):
_ThreadMode.__init__(self, strategy, strategy, None)
class _InReplicaThreadMode(_ThreadMode):
def __init__(self, replica_ctx):
_ThreadMode.__init__(self, replica_ctx.strategy, None, replica_ctx)
def _push_per_thread_mode(context):
ops.get_default_graph()._distribution_strategy_stack.append(context) # pylint: disable=protected-access
def _pop_per_thread_mode():
ops.get_default_graph()._distribution_strategy_stack.pop(-1) # pylint: disable=protected-access
class _DefaultReplicaThreadMode(_ThreadMode):
"""Type of default value returned by `_get_per_thread_mode()`.
Used when the thread-local stack is empty.
"""
def __init__(self):
_ThreadMode.__init__(self, _get_default_strategy(), None,
_get_default_replica_context())
def _get_per_thread_mode():
try:
return ops.get_default_graph()._distribution_strategy_stack[-1] # pylint: disable=protected-access
except (AttributeError, IndexError):
return _get_default_replica_mode()
# ------------------------------------------------------------------------------
# Public API for accessing the current thread mode
@tf_export("distribute.get_replica_context")
def get_replica_context():
"""Returns the current `tf.distribute.ReplicaContext` or `None`.
Returns `None` if in a cross-replica context.
Note that execution:
1. starts in the default (single-replica) replica context (this function
will return the default `ReplicaContext` object);
2. switches to cross-replica context (in which case this will return
`None`) when entering a `with tf.distribute.Strategy.scope():` block;
3. switches to a (non-default) replica context inside
`strategy.experimental_run_v2(fn, ...)`;
4. if `fn` calls `get_replica_context().merge_call(merge_fn, ...)`, then
inside `merge_fn` you are back in the cross-replica context (and again
this function will return `None`).
Most `tf.distribute.Strategy` methods may only be executed in
a cross-replica context, in a replica context you should use the
API of the `tf.distribute.ReplicaContext` object returned by this
method instead.
```
assert tf.distribute.get_replica_context() is not None # default
with strategy.scope():
assert tf.distribute.get_replica_context() is None
def f():
replica_context = tf.distribute.get_replica_context() # for strategy
assert replica_context is not None
tf.print("Replica id: ", replica_context.replica_id_in_sync_group,
" of ", replica_context.num_replicas_in_sync)
strategy.experimental_run_v2(f)
```
Returns:
The current `tf.distribute.ReplicaContext` object when in a replica context
scope, else `None`.
Within a particular block, exactly one of these two things will be true:
* `get_replica_context()` returns non-`None`, or
* `tf.distribute.is_cross_replica_context()` returns True.
"""
return _get_per_thread_mode().replica_context
def get_cross_replica_context():
"""Returns the current tf.distribute.Strategy if in a cross-replica context.
DEPRECATED: Please use `in_cross_replica_context()` and
`get_strategy()` instead.
Returns:
Returns the current `tf.distribute.Strategy` object in a cross-replica
context, or `None`.
Exactly one of `get_replica_context()` and `get_cross_replica_context()`
will return `None` in a particular block.
"""
return _get_per_thread_mode().cross_replica_context
@tf_export("distribute.in_cross_replica_context")
def in_cross_replica_context():
"""Returns `True` if in a cross-replica context.
See `tf.distribute.get_replica_context` for details.
```
assert not tf.distribute.in_cross_replica_context()
with strategy.scope():
assert tf.distribute.in_cross_replica_context()
def f():
assert not tf.distribute.in_cross_replica_context()
strategy.experimental_run_v2(f)
```
Returns:
`True` if in a cross-replica context (`get_replica_context()` returns
`None`), or `False` if in a replica context (`get_replica_context()` returns
non-`None`).
"""
return _get_per_thread_mode().cross_replica_context is not None
@tf_export("distribute.get_strategy")
def get_strategy():
"""Returns the current `tf.distribute.Strategy` object.
Typically only used in a cross-replica context:
```
if tf.distribute.in_cross_replica_context():
strategy = tf.distribute.get_strategy()
...
```
Returns:
A `tf.distribute.Strategy` object. Inside a `with strategy.scope()` block,
it returns `strategy`, otherwise it returns the default (single-replica)
`tf.distribute.Strategy` object.
"""
return _get_per_thread_mode().strategy
@tf_export("distribute.has_strategy")
def has_strategy():
"""Return if there is a current non-default `tf.distribute.Strategy`.
```
assert not tf.distribute.has_strategy()
with strategy.scope():
assert tf.distribute.has_strategy()
```
Returns:
True if inside a `with strategy.scope():`.
"""
return get_strategy() is not _get_default_strategy()
def get_strategy_and_replica_context():
per_thread_mode = _get_per_thread_mode()
return (per_thread_mode.strategy, per_thread_mode.replica_context)
@tf_export("distribute.experimental_set_strategy")
def experimental_set_strategy(strategy):
"""Set a `tf.distribute.Strategy` as current without `with strategy.scope()`.
```
tf.distribute.experimental_set_strategy(strategy1)
f()
tf.distribute.experimental_set_strategy(strategy2)
g()
tf.distribute.experimental_set_strategy(None)
h()
```
is equivalent to:
```
with strategy1.scope():
f()
with strategy2.scope():
g()
h()
```
In general, you should use the `with strategy.scope():` API, but this
alternative may be convenient in notebooks where you would have to put
each cell in a `with strategy.scope():` block.
Note: This should only be called outside of any TensorFlow scope to
avoid improper nesting.
Args:
strategy: A `tf.distribute.Strategy` object or None.
Raises:
RuntimeError: If called inside a `with strategy.scope():`.
"""
old_scope = ops.get_default_graph()._global_distribute_strategy_scope # pylint: disable=protected-access
if old_scope is not None:
old_scope.__exit__(None, None, None)
ops.get_default_graph()._global_distribute_strategy_scope = None # pylint: disable=protected-access
if has_strategy():
raise RuntimeError(
"Must not be called inside a `tf.distribute.Strategy` scope.")
if strategy is not None:
new_scope = strategy.scope()
new_scope.__enter__()
ops.get_default_graph()._global_distribute_strategy_scope = new_scope # pylint: disable=protected-access
# ------------------------------------------------------------------------------
# Defaults that are used when no tf.distribute.Strategy is explicitly created.
# We create them lazily in a function so that we can workaround the circular
# dependency on distribute_lib. See lazy loader at the top of this file.
_defaults = {
"strategy": None,
"replica_context": None,
"replica_mode": None
}
# Note: These need to be different locks since _get_default_replica_context
# calls _get_default_strategy inside its lock, and them using the same lock
# can lead to deadlock.
_default_strategy_lock = threading.Lock()
_default_replica_context_lock = threading.Lock()
_default_replica_mode_lock = threading.Lock()
def _get_default_strategy():
if _defaults["strategy"] is None:
# Avoid race condition causing two defaults to be created
with _default_strategy_lock:
if _defaults["strategy"] is None:
# pylint: disable=protected-access
# Make sure distribute_lib module is loaded by accessing some member.
_ = distribute_lib._creating_default_strategy_singleton
distribute_lib._creating_default_strategy_singleton = True
_defaults["strategy"] = distribute_lib._DefaultDistributionStrategy()
distribute_lib._creating_default_strategy_singleton = False
# pylint: enable=protected-access
return _defaults["strategy"]
def _get_default_replica_context():
if _defaults["replica_context"] is None:
# Avoid race condition causing two defaults to be created
with _default_replica_context_lock:
if _defaults["replica_context"] is None:
_defaults["replica_context"] = distribute_lib.ReplicaContext(
_get_default_strategy(), replica_id_in_sync_group=0)
return _defaults["replica_context"]
def _get_default_replica_mode():
if _defaults["replica_mode"] is None:
# Avoid race condition causing two defaults to be created
with _default_replica_mode_lock:
if _defaults["replica_mode"] is None:
_defaults["replica_mode"] = _DefaultReplicaThreadMode()
return _defaults["replica_mode"]
# Aliases for compatibility with old names.
get_distribution_strategy = get_strategy
has_distribution_strategy = has_strategy